• Journal of Korean Home Economics Education Association
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• v.30 no.3
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• pp.19-42
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• 2018

The purpose of this study is to analyze the tasks of 'dietary life' in the textbook developed according to the 2015 revised middle school 「Technology·Home economics」 education curriculum based on the multiple intelligence teaching and learning methods. To accomplish this purpose, 12 textbooks of middle school 「Technology·Home economics」 textbooks were titled "Nutrition and Dietary Behavior of Adolescents", "Planning and Choosing Meals", "Choosing Foods and Safe Cooking" except the questions, the tasks that the students can perform are analyzed based on the teaching and learning methods using multiple intelligences. Analysis methods were analyzed by using contents analysis method, focusing on learning activities, and sub-questions of activities were all included in each activity, and the process of preparing activities on a continuous line was grouped into one. Three people analyzed the activities and proceeded to revise and supplement the analysis standard through consultation. The other three researchers confirmed it. As a result of analyzing 12 kinds of textbooks, the number of activity tasks was 25~74 for each kind of textbooks, and the total number of activities was 527. According to the ratio of multiple intelligences, 35% of the tasks were using logical-mathematical intelligence, and 26.8% of linguistic intelligence, 23% of intrapersonal intelligence, 7.2% of interpersonal intelligence, 3.8% of spatial intelligence, bodily-kinesthetic(2.7%) and musical intelligence(1.5%). On the other hand, it was analyzed that there is no activity task using naturalist intelligence. Except to the naturalist intelligence, general intelligence was utilized. This indicates that the home economics curriculum is a convergence of the home economics curriculum in that it is a reorganization by extracting the contents and methods of other curriculum related to dietary life, is interpreted. This study is expected to provide a framework for various teaching and learning methods to activate students' participation classes and to provide an alternative to realize convergence education in home economics curriculum.

• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.67-101
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• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.578-589
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• 2018

Building Integrated Photovoltaic (BIPV) system is a typical integrated system that simultaneously performs both building function and solar power generation function. To maximize its potential advantage, however, the solar photovoltaic power generation function must be integrated from the early conceptual design stage, and maximum power generation must be designed. To cope with such requirements, preliminary research on BIPV design process based on architectural design model and computer simulation results for improving solar power generation performance have been published. However, the requirements of the BIPV system have not been clearly identified and systematically reflected in the subsequent design. Moreover, no model has verified the power generation design. To solve these problems, we systematically model the requirements of BIPV system and study power generation design based on the system requirements model. Through the study, we consistently use the standard system modeling language, SysML. Specifically, stakeholder requirements were first identified from stakeholders and related BIPV standards. Then, based on the domain model, the design requirements of the BIPV system were derived at the system level, and the functional and physical architectures of the target system were created based on the system requirements. Finally, the power generation performance of the BIPV system was evaluated through a simulated SysML model (Parametric diagram). If the SysML system model developed herein can be reinforced by reflecting the conditions resulting from building design, it will open an opportunity to study and optimize the power generation in the BIPV system in an integrated fashion.

• Journal of the Korean Applied Science and Technology
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• v.37 no.5
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• pp.1390-1401
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• 2020

This study is a descriptive research to identify the relationship among violence experience, resilience and job stress of nurses working in emergency department. The subjects of this study were 143 nurses with over one year working in emergency departments of 6 hospitals located in D city and C city and collected data through structured questionnaire. It was from November 6th to November 15th. The degree of violent experience of the subjects was 1.26 ± 1.31 out of 4. The average score of resillience was 2.50 ± 0.55 out of 4. The average score of job stress was 3.62 ± 0.49 out of 5. The result of correlation between violence experience, resilience and job stress, among the sub factors, in the correlation among violence experience and job stress sub factors, verbal violence experience was significantly positively correlated with nursing work(r=.194, p=.010), role conflict stress(r=.158, p=.030), and physical threat experience was positively correlated with nursing work(r=.200, p=.008), role conflict(r=.162, p=.027), and conflict with doctor(r=.145, p=.042). In the correlation between resilience and job stress sub factors, nursing work stress is hardness(r=-.189, p=.012), persistence(r=-.165, p=.025), and optimism (r=-.186, p=.013) and there was a negative correlation with the region. Expertise stress is hardness(r=-.230, p=.003), persistence(r=-.195, p=.010), optimistic(r=-.194, p=.010) and there was a negative correlation. Nurse-treated stress was positively correlated with spirituality(r=.154, p=.033). In the subcategory correlations of resilience and violent experience, the hardness had a negative correlation with the physical threat(r=-.150, p=.037) experience. The persistence was negatively correlated with the experience of physical threats(r=-.138, p=.050). The optimism was negatively correlated with the experience of physical violence(r=-.151, p=.036). As a result, it is necessary to create a safe working environment free from violence and to reinforce training on how to deal with violence in order to reduce the job stress of emergency department nurses. In addition, measures to cope with stress according to age and work experience and programs to increase resilience should be developed and mediated to reduce the job stress of emergency department nurses.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.253-266
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• 2018

This paper proposes a methodology applying sequence tagging methodology to improve the performance of NER(Named Entity Recognition) used in QA system. In order to retrieve the correct answers stored in the database, it is necessary to switch the user's query into a language of the database such as SQL(Structured Query Language). Then, the computer can recognize the language of the user. This is the process of identifying the class or data name contained in the database. The method of retrieving the words contained in the query in the existing database and recognizing the object does not identify the homophone and the word phrases because it does not consider the context of the user's query. If there are multiple search results, all of them are returned as a result, so there can be many interpretations on the query and the time complexity for the calculation becomes large. To overcome these, this study aims to solve this problem by reflecting the contextual meaning of the query using Bidirectional LSTM-CRF. Also we tried to solve the disadvantages of the neural network model which can't identify the untrained words by using ontology knowledge based feature. Experiments were conducted on the ontology knowledge base of music domain and the performance was evaluated. In order to accurately evaluate the performance of the L-Bidirectional LSTM-CRF proposed in this study, we experimented with converting the words included in the learned query into untrained words in order to test whether the words were included in the database but correctly identified the untrained words. As a result, it was possible to recognize objects considering the context and can recognize the untrained words without re-training the L-Bidirectional LSTM-CRF mode, and it is confirmed that the performance of the object recognition as a whole is improved.

• Progress in Medical Physics
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• v.3 no.2
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• pp.1-12
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• 1992

For intraoperative radiation therapy using electron beams, a cone system to deliver a large dose to the tumor during surgical operation and to save the surrounding normal tissue should be developed and dosimetry for the cone system is necessary to find proper X-ray collimator setting as well as to get useful data for clinical use. We developed a docking type of a cone system consisting of two parts made of aluminum: holder and cone. The cones which range from 4cm to 9cm with 1cm step at 100cm SSD of photon beam are 28cm long circular tubular cylinders. The system has two 26cm long holders: one for the cones larger than or equal to 7cm diamter and another for the smaller ones than 7cm. On the side of the holder is an aperture for insertion of a lamp and mirror to observe treatment field. Depth dose curve. dose profile and output factor at dept of dose maximum. and dose distribution in water for each cone size were measured with a p-type silicone detector controlled by a linear scanner for several extra opening of X-ray collimators. For a combination of electron energy and cone size, the opening of the X-ray collimator was caused to the surface dose, depths of dose maximum and 80%, dose profile and output factor. The variation of the output factor was the most remarkable. The output factors of 9MeV electron, as an example, range from 0.637 to 1.549. The opening of X-ray collimators would cause the quantity of scattered electrons coming to the IORT cone system. which in turn would change the dose distribution as well as the output factor. Dosimetry for an IORT cone system is inevitable to minimize uncertainty in the clinical use.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.147-156
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• 2022

The purpose of this study was to review various grounds and plans for the establishment of a convergence major in lifelong education for the disabled based on Daegu University, which establishes its status and identity as a base university for education and welfare for the disabled. Lifelong education for the disabled reflects the specificity of disability in common because it targets disabled learners, but since it constitutes two perspectives and characteristics of education and welfare, access to interdisciplinary convergence research in disabled-related fields is important. In the above dimension, Daegu University has an appropriate foundation to lead lifelong education for the disabled in Korea through various academic and practice-based infrastructures, and has sufficient leadership to improve the practical limitations of the lifelong education support system for the disabled. Accordingly, this study presented measures and related grounds to reflect lifelong education for the disabled in order to establish an interdisciplinary convergence major at Daegu University through literature review and expert advice. It was emphasized that lifelong education for the disabled, viewed as a new interdisciplinary convergence major, should be activated through professional competencies commonly accessible to the three fields rather than applied from a priority perspective between special education, rehabilitation science, and social welfare. As a result of the study, it was suggested that Korea, which failed to establish a lifelong education support system for the disabled, should gradually spread and spread to other universities starting with Daegu University's application model and plan. In addition, the necessity of systematically establishing a qualification development path for lifelong education professionals for the disabled through agreement between the three fields was also suggested.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.2
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• pp.36-42
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• 2011

The current healthcare information systems field to meet the growing demand for healthcare for a variety of building systems and operation, and subsequent information on the budget continues to increase, but the current system, although the association link between the various systems made does not, with organizations with information about each of the standardization and real-time network status data do not consist of various materials, such as insufficient to provide real-time issues have been raised. This paper proposes a Integrated information system on Healthcare based on JXTA to solve problems mentioned above. Until now, in a network environment for data storage and management is the most widely used server-intensive structure, while an increase in users and traffic difficulties in data management and communications services to handle the growing number of servers increase faster than information associated with the cost savings, P2P model in terms of efficient data management has emerged as a new solution. Therefore this paper designs a platform for Integrated information system on Healthcare based on JXTA as a method to integrate health information data and services, and then proves that the new information system on healthcare based on JXTA is the suitable model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.26-32
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• 2008

Video compression schemes have been developed and used for many years. Currently, H.264/AVC is the most efficient video coding standard. The H.264/AVC baseline profile adopts CAVLC(Context-Adaptive Variable Length Coding) method as an entropy coding method. CAVLC gives better performance in compression ratios than conventional VLC(Variable Length Coding). However, because CAVLC decoder uses a lot of VLC tables, the CAVLC decoder requires a lot of area in terms of hardware. Conversely, since it must look up the VLC tables, it gives a worse performance in terms of software. In this paper, we propose a new hierarchical grouping method for the VLC tables. We can obtain an index of codes in the reconstructed VLC tables by simple arithmetic operations. In this method, the VLC tables are accessed just once in decoding a symbol. We modeled the proposed algorithm in C language, compiled under ARM ADS1.2 and simulated it with Armulator. Experimental results show that the proposed algorithm reduces execution time by about 80% and 15% compared with the H.264/AVC reference program JM(Joint Model) 10.2 and the arithmetic operation algorithm which is recently proposed, respectively.